{ \renewcommand{\arraystretch}{1.2} 
\begin{table} 
\center 
\begin{tabular}{ccc cc cc} 
\hline 
 & && DA KSC & DA RW & HMM fix & HMM adapt \\ \hline  \hline
 \multicolumn{2}{c}{time (s)}& & 16.2941  & 19.3464  & 358.0721  & 394.1615  \\  \hline 
\multicolumn{7}{c}{$\theta$} \\ \hline 
\multirow{4}{*}{$\mu$}   & mean  &   & -0.0647  & 0.0060  & -0.0793  & -0.0762  \\ [0.75ex]
 & std  &   & (0.0774)  & (0.1577)  & (0.0757)  & (0.0743)  \\ [0.75ex]
 & ESS  &   & 327.1624  & 4.4464  & 681.8437  & 629.1132  \\ [0.75ex]
 & AR && --  & 0.3397  & 0.3413  & 0.3372  \\ [1.3ex] 
\multirow{4}{*}{$\phi$}   & mean  &   & 0.8332  & 0.8637  & 0.8299  & 0.8217  \\ [0.75ex]
 & std  &   & (0.0325)  & (0.0639)  & (0.0370)  & (0.0369)  \\ [0.75ex]
 & ESS  &   & 45.8660  & 4.1256  & 37.7016  & 57.7771  \\ [0.75ex]
 & AR && --  & 0.3262  & 0.3069  & 0.3047  \\ [1.3ex] 
\multirow{4}{*}{$\sigma^2$}   & mean  &   & 0.2309  & 0.1705  & 0.2343  & 0.2515  \\ [0.75ex]
 & std  &   & (0.0473)  & (0.1158)  & (0.0566)  & (0.0552)  \\ [0.75ex]
 & ESS  &   & 36.5339  & 3.8662  & 35.2696  & 49.3356  \\ [0.75ex]
 & AR && --  & 0.2883  & 0.3220  & 0.3358  \\ [1.3ex] 
\hline 
\multicolumn{7}{c}{$ \bm{h} $} \\ \hline 
\multirow{4}{*}{$h_{200}$}   & mean &   & 0.5237  & 0.3793  & 0.4798  & 0.4749  \\ [0.75ex]
 & std &   & (0.5894)  & (0.5215)  & (0.5918)  & (0.6064)  \\ [0.75ex]
 & ESS  &   & 290.0201  & 167.9406  & 797.2938  & 602.5589  \\ [1.3ex] 
\multirow{4}{*}{$h_{600}$}   & mean &   & -1.1906  & -0.8056  & -1.2174  & -1.1787  \\ [0.75ex]
 & std &   & (0.6537)  & (0.8265)  & (0.6928)  & (0.6863)  \\ [0.75ex]
 & ESS  &   & 206.4936  & 7.9383  & 533.8303  & 602.5731  \\ [1.3ex] 
\multirow{4}{*}{$h_{1000}$}   & mean &   & 0.2376  & 0.2201  & 0.2472  & 0.2506  \\ [0.75ex]
 & std &   & (0.5071)  & (0.4655)  & (0.4951)  & (0.5090)  \\ [0.75ex]
 & ESS  &   & 164.3796  & 113.7029  & 817.9247  & 724.0934  \\ [1.3ex] 
\multirow{4}{*}{$h_{1400}$}   & mean &   & 0.0277  & 0.0825  & 0.0130  & 0.0083  \\ [0.75ex]
 & std &   & (0.6357)  & (0.5237)  & (0.6049)  & (0.6043)  \\ [0.75ex]
 & ESS  &   & 169.6950  & 19.8537  & 594.3385  & 748.5398  \\ [1.3ex] 
\multirow{4}{*}{$h_{1800}$}   & mean &   & 0.5935  & 0.5499  & 0.5865  & 0.5846  \\ [0.75ex]
 & std &   & (0.5389)  & (0.5001)  & (0.5393)  & (0.5439)  \\ [0.75ex]
 & ESS  &   & 364.6283  & 48.0346  & 1056.3624  & 882.2105  \\ [1.3ex] 
 & AR & & --  & 0.3372  & 0.3584  & 0.3314 \\ \hline 
\hline 
\multicolumn{7}{p{11cm}}{\footnotesize{ESS: effective sample size at lag equal to the lowest order at which sample autocorrelation is not significant.}}  \\ 
\multicolumn{7}{p{11cm}}{\footnotesize{AR: acceptance rate of the MH RW algorithm. (for $h_{t}$ average over imputations)}}  \\ 
\end{tabular}
 \caption{Posterior means, standard deviations, effective sample sizes (ESS)  for $M=10000$ posterior draws after a burn-in of $10000$ for $T=2000$ observations of \textbf{IBM} data.}
\label{tab:SV_results_IBM}  
\end{table}
}